CAREER: CAS- Climate -- Air-quality-related environmental justice impacts of decarbonization scenarios

职业：CAS-气候——脱碳情景与空气质量相关的环境正义影响

• 批准号: 2339462
• 负责人: Christopher Tessum
• 金额: $ 51万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-01 至 2028-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2339462&HistoricalAwards=false
• 关键词: CAREER; CAS; Climate; Air; quality; CAREER; CAS; Climate; Air; quality

The U.S. and other nations are at the beginning of a major technological shift from a fossil fuel-based economy to one driven by non-climate-forcing energy generation. The speed and success of this technology shift (“decarbonization”) depend in part upon whether it is perceived to be implemented equitably with benefits that accrue broadly across society. A major way that energy generation intersects with equity is through ambient air pollution. Ambient air pollution is one of the largest causes of death in the US and globally, with health burdens that are distributed inequitably on both regional and international scales. However, minimal research has thus far been conducted into the air quality and environmental justice implications of different decarbonization strategies. Furthermore, current integrated assessment models, which are used to develop decarbonization strategies, have minimal support for air quality assessment and are not well-suited to quantify environmental inequity. This project will develop a new modeling framework for integrated assessment of climate, air quality, and environmental equity impacts of policy scenarios, and apply the framework in the analysis and evaluation of climate policy. The research targets greatly improved understanding of the co-benefits and dis-benefits of decarbonization policy scenarios, especially as related to environmental equity, both within the US and internationally. It also targets improved understanding of effective methods for educating the general public on climate science and policy. The open-source computational tools to be created aim to facilitate the calculation of air quality co-benefits and related equity by policymakers, sustainability scientists, and others. This goal is to result in a stronger technical grounding for decarbonization policy. Furthermore, as the perception of equity is critical to successful decarbonization, the identification of strategies that mitigate environmental injustice, and the development of educational tools to broadly communicate the benefits of those policies, will contribute to the fight against climate change overall. Project research will be organized in three Thrusts. Thrust 1 will couple the Global Change Analysis Model (GCAM) with the Intervention Model for Air Pollution (InMAP). GCAM represents linkages between energy, water, land, climate and economic systems. InMAP is a high-resolution, reduced-complexity model of the transport, transformation, and removal of air pollution developed by PI Tessum and widely used to estimate air pollution health and equity impacts of policy interventions. Both GCAM and InMAP have versions that are global- and US-focused and the research will couple the corresponding versions to allow analysis at sub-national US and international scales. Thrust 2 will expand the coupled models developed in Thrust 1 to allow high-resolution integrated assessment. To do this, the research will integrate high-resolution demographic population down-scaling into the resulting model to allow the assessment of how policy scenarios will differentially affect air pollution exposure across different demographic groups. Technology implementation decisions will also be enabled at high spatial resolution within the model, enabling the exploration of intra-urban location-based policy implementation. Thrust 3 will create a machine-learned single-pass GCAM solver that allows the model to run in seconds instead of hours for a subset of possible scenarios, as well as flexible software infrastructure (GCAM-EDU) for building interactive educational experiences.This CAREER project is jointly supported by the NSF ENG/CBET Environmental Sustainability and Environmental Engineering program.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

美国和其他国家正处于从化石燃料基于非气候燃料的能源发电驱动的一项重大技术转变。这种技术转变的速度和成功（“脱碳”）部分取决于它是否被认为是同等地实施的，其利益在整个社会之间广泛带来。能源发电与公平相交的主要方式是通过环境空气污染。环境空气污染是美国和全球最大的死亡原因之一，其健康伯伦斯在区域和国际规模上分布不当。但是，到目前为止，对不同脱碳策略的空气质量和环境正义含义进行了最低限度的研究。此外，用于制定脱碳策略的当前综合评估模型对空气质量评估的支持最少，并且不适合量化环境不平等。该项目将开发一个新的建模框架，用于对政策情景的气候，空气质量和环境平等影响的整合评估，并将框架应用于气候政策的分析和评估中。该研究大大提高了对脱碳政策情景的共同利益和散发性的理解，尤其是与美国境内和国际上的环境公平有关的。还可以提高对有效方法教育气候科学和政策的有效方法的理解。要创建的开源计算工具旨在准备决策者，可持续性科学家等对空气质量共同利益和相关权益的计算。这个目标是为脱碳而产生更强大的技术基础。此外，由于对公平的看法对于成功的脱碳至关重要，减轻环境伤害的策略的识别以及开发教育工具以广泛传达这些政策的益处，这将有助于打击气候变化的整体斗争。项目研究将分为三个推力。推力1将将全球变化分析模型（GCAM）与空气污染的干预模型（INMAP）息息。 GCAM代表能源，水，土地，气候和经济体系之间的联系。 Inmap是一种高分辨率的，减少的复杂性模型的运输，转化和清除由Pi Tessum开发的空气污染，并广泛用于估计空气污染健康和政策干预的公平影响。 GCAM和INMAP都具有全球性和美国为中心的版本，该研究将对相应的版本进行配对以允许在美国和国际范围内进行分析。推力2将扩大推力1中开发的耦合模型，以允许高分辨率集成评估。为此，该研究将将高分辨率人口群体缩减到最终的模型中，以允许评估政策情景如何不同地影响不同人口组的空气污染暴露。技术实施决策还将在模型中的高空间分辨率下启用，从而探索基于城市内部位置的政策实施。 Thrust 3 will create a machine-learned single-pass GCAM solver that allows the model to run in seconds instead of hours for a subset of possible scenarios, as well as flexible software infrastructure (GCAM-EDU) for building interactive educational experiences.This CAREER project is jointly supported by the NSF ENG/CBET Environmental Sustainability and Environmental Engineering program.This award reflects NSF's statutory mission and has been deemed值得通过基金会的智力优点和更广泛的影响审查标准来通过评估来支持。